olink_heatmap_plot: Function to plot a heatmap of the NPX data

In OlinkAnalyze: Facilitate Analysis of Proteomic Data from Olink

Function to plot a heatmap of the NPX data

Description

Generates a heatmap using pheatmap::pheatmap of all samples from NPX data.

Usage

olink_heatmap_plot(
  df,
  check_log = NULL,
  variable_row_list = NULL,
  variable_col_list = NULL,
  center_scale = TRUE,
  cluster_rows = TRUE,
  cluster_cols = TRUE,
  show_rownames = TRUE,
  show_colnames = TRUE,
  colnames = "both",
  annotation_legend = TRUE,
  fontsize = 10,
  na_col = "black",
  ...
)

Arguments

df	Data frame in long format with SampleID, NPX, OlinkID, Assay and columns of choice for annotations.
check_log	output from check_npx on df
variable_row_list	Columns in df to be annotated for rows in the heatmap.
variable_col_list	Columns in df to be annotated for columns in the heatmap.
center_scale	Logical. If data should be centered and scaled across assays (default TRUE).
cluster_rows	Logical. Determining if rows should be clustered (default TRUE).
cluster_cols	Logical. Determining if columns should be clustered (default TRUE).
show_rownames	Logical. Determining if row names are shown (default TRUE).
show_colnames	Logical. Determining if column names are shown (default TRUE).
colnames	Character. Determines how to label the columns. Must be 'assay', 'oid', or 'both' (default 'both').
annotation_legend	Logical. Determining if legend for annotations should be shown (default TRUE).
fontsize	Fontsize (default 10)
na_col	Color of cells with NA (default black)
...	Additional arguments used in pheatmap::pheatmap

Details

The values are by default scaled across and centered in the heatmap. Columns and rows are by default sorted by by dendrogram. Unique sample names are required.

Value

An object of class ggplot, generated from the gtable returned by pheatmap::pheatmap.

Examples

if (rlang::is_installed(pkg = c("ggplotify", "pheatmap"))) {
  npx_data <- npx_data1 |>
    dplyr::filter(
      !stringr::str_detect(
        string = .data[["SampleID"]],
        pattern = "CONT"
      )
    )
  check_log <- OlinkAnalyze::check_npx(
    df = npx_data
  )

  # Heatmap
  OlinkAnalyze::olink_heatmap_plot(
    df = npx_data,
    check_log = check_log
  )

  # Heatmap with annotation
  OlinkAnalyze::olink_heatmap_plot(
    df = npx_data,
    check_log = check_log,
    variable_row_list = c("Time", "Site")
  )

  # Heatmap with calls from pheatmap
  OlinkAnalyze::olink_heatmap_plot(
    df = npx_data,
    check_log = check_log,
    cutree_rows = 3L
  )
}

OlinkAnalyze documentation built on June 24, 2026, 1:06 a.m.